¶ OpenShift
¶ Dev Ops
¶ Introduction to OpenShift: A Modern Platform for Cloud-Native DevOps at Scale
There is a point in every organization’s technology journey when the old ways of deploying software no longer fit the speed, complexity, or ambition of the business. Applications become more distributed. Teams become more specialized. Deployments become more frequent. And the traditional infrastructure model—where everything is configured manually and maintained through a patchwork of scripts—begins to show its limits. This is the environment that gave rise to containerized applications and orchestration platforms. And among the platforms built to support this shift, OpenShift stands out as a powerful, enterprise-grade environment that brings order, automation, and clarity to cloud-native development.
OpenShift is often described as Red Hat’s enterprise Kubernetes platform, but that description barely scratches the surface. Yes, Kubernetes is at the core, providing container orchestration, scaling, scheduling, and service discovery. But OpenShift adds layers of usability, security, governance, and developer experience that transform Kubernetes from a highly flexible but complex system into a polished, production-ready platform. It’s a system that understands not just how applications run, but how teams work, how enterprises govern, and how DevOps pipelines operate.
While Kubernetes gives you the raw power to deploy containers at scale, OpenShift gives you an environment where those containers can thrive. It bundles together everything teams need to build, deploy, monitor, and manage applications reliably—source-to-image workflows, integrated CI/CD capabilities, image security scanning, role-based access control, automated upgrades, centralized logging, service mesh options, and built-in developer tooling. In doing so, OpenShift becomes more than a cluster manager; it becomes a complete operating system for cloud-native development.
The reason OpenShift resonates so strongly with DevOps teams is that it embraces the entire lifecycle of software delivery. Instead of treating infrastructure, pipelines, code, and deployments as separate worlds, it pulls them into a unified flow. Developers push code, OpenShift builds the container image, deploys the application, monitors it, and keeps it running. Operations teams gain an environment that enforces consistent security and governance without slowing innovation. Leaders gain visibility into how applications progress through the pipeline. This alignment across roles is one of the deepest values of a DevOps culture—and OpenShift was designed with this mindset from the start.
One of the most immediate benefits teams notice when they begin using OpenShift is how it removes friction from everyday tasks. For example, provisioning environments no longer requires tickets and manual configuration. Developers can create their own project spaces, spin up services, deploy applications, and iterate quickly. CI/CD pipelines can be triggered automatically on commit. Container builds are handled by the platform rather than relying on ad-hoc scripts. Every part of the process becomes faster, more predictable, and more consistent.
And while many Kubernetes distributions require deep knowledge of YAML, manifests, networking models, and cluster internals, OpenShift softens this learning curve. It provides a polished web console, intuitive CLI tools, preconfigured defaults, and developer-friendly abstractions that make the platform easier to navigate. This is especially important for organizations transitioning to cloud-native development for the first time. Instead of expecting every team member to be an expert in Kubernetes internals, OpenShift enables them to focus on delivering value.
Security is another area where OpenShift has a significant impact. Kubernetes itself is extremely powerful but also highly configurable, and misconfiguration can lead to vulnerabilities. OpenShift takes a strong stance here. It applies security policies out of the box that many organizations would otherwise need to design themselves. It restricts containers from running as root, manages certificate rotation, controls registry access, and ensures workloads remain isolated. For enterprises dealing with compliance, regulation, and risk, these guardrails are not just helpful—they’re essential.
Just as important as security is the idea of consistency. One of the challenges of working with containers is managing the diversity of environments—local machines, testing clusters, staging environments, production clusters. OpenShift strives to make these environments feel cohesive. The same tools, commands, APIs, and behaviors apply regardless of whether you’re working on a laptop, a private datacenter, or a multi-region cloud deployment. This consistency makes it easier to reproduce issues, replicate environments, and maintain stability even as applications scale.
The operational advantages of OpenShift become even more pronounced at scale. As companies grow, so do their clusters, their teams, and their workloads. Managing upgrades, cluster health, networking, observability, and policies manually becomes tedious and error-prone. OpenShift automates much of this. Cluster upgrades become routine rather than stressful events. Operators automate infrastructure tasks that would normally require manual intervention. Logging and monitoring become integrated experiences rather than patch-together solutions. And because OpenShift itself is built around operators, many essential services self-manage in the same way.
This automation is especially valuable for workloads that must run reliably across multiple clusters or data centers. OpenShift supports hybrid-cloud and multi-cloud deployments natively, making it possible to run workloads across on-premise datacenters, public cloud providers, or edge environments with consistent control and governance. Many organizations choose OpenShift precisely because they want flexibility—they want to embrace the cloud but avoid being tied to a single vendor. OpenShift gives them that freedom.
A core principle of DevOps is enabling developers to own their work end-to-end—from writing code to deploying and monitoring it in production. OpenShift supports this through its source-to-image (S2I) capabilities, integrated pipeline tools, and strong support for GitOps models. Rather than requiring developers to manage Dockerfiles or build scripts manually, OpenShift can automatically build images from source code repositories. This reduces cognitive load and helps teams adopt practices that lead to consistency and automation.
GitOps, in particular, has become a growing trend in the DevOps world, and OpenShift embraces it wholeheartedly. By storing application configuration in version control, teams gain the ability to roll back changes, track history, and automate deployments through commit-driven workflows. This works seamlessly with tools like Argo CD and Tekton, which are increasingly becoming part of the OpenShift ecosystem. With Git as the source of truth, infrastructure drift becomes a thing of the past, and deployment pipelines become predictable rather than mysterious.
Throughout this course, you’ll explore the many layers of OpenShift in depth. You’ll learn how to deploy clusters, build containers, manage operators, design microservices architectures, secure workloads, configure CI/CD pipelines, monitor applications, troubleshoot issues, and architect resilient systems. You will understand how OpenShift differs from vanilla Kubernetes, when to use its advanced features, how to customize it to your organization’s workflow, and how to integrate it into broader DevOps ecosystems.
Along the way, you’ll deepen your understanding of cloud-native principles such as immutability, declarative configuration, horizontal scaling, service meshes, and container security. You’ll see how these ideas influence modern software design and how OpenShift provides the tools to implement them thoughtfully. You will also gain practical insights into scaling applications, handling failures gracefully, optimizing resource usage, and delivering features at a pace that matches the expectations of the modern digital world.
OpenShift is more than a platform—it’s a bridge between technology and teamwork. It allows developers to collaborate more effectively, enables operations teams to automate more intelligently, and gives organizations the confidence to innovate without fear of breaking everything. It reflects the aspirations of cloud-native DevOps: speed, stability, automation, and continuous improvement.
Perhaps the most important thing to understand about OpenShift is that it represents the convergence of many years of evolution in DevOps thinking. Early DevOps was about removing silos and increasing collaboration. Kubernetes introduced powerful abstractions for running containerized applications. OpenShift builds on these foundations and brings them together into a cohesive, enterprise-ready solution that teams can trust.
As you progress through these 100 articles, OpenShift will shift in your mind from a tool to an ecosystem—from something that runs containers to something that empowers teams. You will come to appreciate its depth, its flexibility, its design decisions, and its role in shaping how modern organizations build and run software. And by the end of this journey, you’ll be able to leverage OpenShift not just as a cluster platform, but as a cornerstone of your DevOps practice.
OpenShift’s story is ultimately a story about scaling—not just systems, but collaboration, innovation, and confidence. It gives teams the environment they need to build boldly, release continuously, operate safely, and learn relentlessly. And in the fast-paced world of modern software development, that combination is invaluable.
¶ OpenShift
¶ Part 1: Introduction to OpenShift and DevOps Fundamentals
1. What is OpenShift? An Introduction to Kubernetes-based Platforms
2. The Role of OpenShift in DevOps: Benefits and Use Cases
3. Understanding the OpenShift Architecture
4. Setting Up OpenShift: Installation and Initial Configuration
5. Navigating the OpenShift Web Console and CLI
6. Key Concepts of OpenShift: Projects, Pods, and Namespaces
7. OpenShift vs Kubernetes: Key Differences for DevOps Teams
8. Creating Your First OpenShift Application
9. Managing OpenShift Clusters: Best Practices
10. Using OpenShift for Continuous Integration and Delivery (CI/CD)
¶ Part 2: OpenShift Core Concepts
11. Understanding OpenShift Projects and Namespaces
12. Creating and Managing OpenShift Pods
13. Exploring OpenShift Deployment Configurations
14. Understanding OpenShift Services and Routes
15. Managing OpenShift ConfigMaps and Secrets
16. Understanding OpenShift Persistent Storage and Volumes
17. The OpenShift Network: Services, Routes, and Networking
18. OpenShift ReplicaSets and Deployments for Scaling
19. Managing Logs and Monitoring in OpenShift
20. Security Best Practices in OpenShift
¶ Part 3: OpenShift for Continuous Integration (CI)
21. Automating Builds with OpenShift BuildConfig
22. Using Jenkins in OpenShift for CI Pipelines
23. Managing Source-to-Image (S2I) Builds in OpenShift
24. Using OpenShift Pipelines (Tekton) for CI/CD
25. Creating Build Triggers and Webhooks in OpenShift
26. Handling Build Failures and Debugging Build Issues
27. Integrating OpenShift with GitLab for Source Code Management
28. Optimizing OpenShift CI for Fast Feedback
29. Implementing Unit Tests in OpenShift CI Pipelines
30. Creating Custom OpenShift Build Strategies
¶ Part 4: OpenShift for Continuous Delivery/Deployment (CD)
31. Using OpenShift DeploymentConfig for Application Deployments
32. Managing Blue-Green and Canary Deployments in OpenShift
33. Automating Rollback Strategies in OpenShift Deployments
34. Using OpenShift Routes for Application Exposing
35. Managing Deployment Strategies in OpenShift
36. Handling Continuous Deployment in OpenShift with Jenkins Pipelines
37. Automating Database Migrations with OpenShift
38. Managing Staging and Production Environments in OpenShift
39. Scaling OpenShift Applications: Horizontal and Vertical Scaling
40. Automating Application Rollouts with OpenShift
¶ Part 5: Advanced OpenShift Concepts
41. OpenShift Operator Framework: Introduction and Use Cases
42. Developing Custom Operators in OpenShift
43. Using OpenShift with Kubernetes Custom Resources (CRDs)
44. Advanced OpenShift Networking: NetworkPolicies and Ingress Controllers
45. High Availability Clusters in OpenShift
46. OpenShift for Multi-Tenant Environments
47. Managing Secrets and Configurations at Scale
48. OpenShift Cluster Monitoring and Alerting with Prometheus
49. Advanced Security Features in OpenShift
50. Integrating OpenShift with External Secrets Managers
¶ Part 6: OpenShift for DevOps Automation
51. Automating Infrastructure as Code (IaC) with OpenShift
52. Using Ansible to Manage OpenShift Resources
53. OpenShift CI/CD Pipelines Automation with Jenkins X
54. Automating Cloud-native Application Deployments with OpenShift
55. Automating Microservices Management with OpenShift
56. Using Helm Charts in OpenShift for Application Deployment
57. Managing OpenShift Resources with kubectl and oc CLI
58. Infrastructure Scaling Automation in OpenShift
59. Automating Monitoring and Logging in OpenShift
60. Automating Security Audits in OpenShift
¶ Part 7: OpenShift for Cloud-Native DevOps
61. Cloud-Native Architecture and OpenShift: Best Practices
62. Deploying Microservices with OpenShift
63. OpenShift and Kubernetes: Best Practices for Cloud-Native Applications
64. Implementing Service Mesh with OpenShift and Istio
65. Managing Cloud-Native Databases in OpenShift
66. Scaling and Auto-Scaling Applications in OpenShift
67. Using OpenShift for Serverless Architectures
68. Leveraging OpenShift for Multi-Cloud Environments
69. Cloud-Native Monitoring with OpenShift and Prometheus
70. Managing Continuous Integration and Deployment for Cloud-Native Apps
¶ Part 8: OpenShift Security for DevOps
71. Securing OpenShift Clusters: User Management and RBAC
72. Using OpenShift Security Contexts for Container Security
73. Managing Network Security in OpenShift with NetworkPolicies
74. OpenShift Security for Microservices Architectures
75. Implementing Encryption and TLS in OpenShift
76. Automating Vulnerability Scanning in OpenShift Pipelines
77. Role-Based Access Control (RBAC) in OpenShift for DevOps Teams
78. Managing Secrets and Sensitive Data in OpenShift
79. Hardening OpenShift Clusters: Best Security Practices
80. Advanced Identity and Access Management in OpenShift
¶ Part 9: OpenShift for Monitoring and Observability
81. Implementing Monitoring with OpenShift’s Prometheus and Grafana
82. Using OpenShift Logs for Troubleshooting and Debugging
83. Setting Up Distributed Tracing with OpenShift and Jaeger
84. Integrating OpenShift with ELK Stack for Centralized Logging
85. Alerting and Notifications in OpenShift
86. Performance Monitoring in OpenShift Clusters
87. Using OpenShift to Monitor Microservices in DevOps
88. Scaling Observability Solutions in OpenShift
89. Analyzing Logs and Metrics for DevOps Teams
90. Integrating OpenShift Monitoring with Third-Party Tools
¶ Part 10: Advanced OpenShift Practices
91. Managing Multi-Cluster Environments with OpenShift
92. Optimizing OpenShift for Large-Scale Enterprise Deployments
93. OpenShift Cluster Upgrades and Rolling Updates
94. Using OpenShift for Cross-Cluster Application Deployments
95. Implementing GitOps with OpenShift and Argo CD
96. Building and Managing OpenShift Data Pipelines
97. Serverless Computing on OpenShift with Knative
98. Building an OpenShift Data Lake for Big Data Applications
99. Using OpenShift for Machine Learning and AI Workflows
100. Future Trends: OpenShift in the Evolving DevOps Landscape